df = df.set_index('timestamp')
print(df.head())

timestamp            id                         value
2018-12-31 23:00:00  5c8fea84763aae175afda38b   98.587768
2018-12-31 23:10:00  5c8fea84763aae175afda38b  107.232742
2018-12-31 23:20:00  5c8fea84763aae175afda38b  104.224153
2018-12-31 23:30:00  5c8fea84763aae175afda38b  104.090750
2018-12-31 23:40:00  5c8fea84763aae175afda38b   99.357023

df = df.resample('D').agg(['min', 'max', 'mean'], columns=['value'])

timestamp   min        max         mean
2018-12-31  98.587768  107.641060  103.522250
2019-01-01  88.396180  109.506622  100.135128
2019-01-02  85.857570  112.420754   99.839120
2019-01-03  87.565014  113.419561   99.734654
2019-01-04  88.902704  112.186989   99.764259

df.resample('D').agg({'id': 'first', 'value': ['mean', 'max']})

                                  id       value
                               first        mean         max
timestamp
2018-12-31  5c8fea84763aae175afda38b  102.698487  107.232742